Google has officially launched Gemini 3.1 Flash-Lite, positioning it as the fastest and most cost-efficient model in the Gemini 3 series. The model delivers 2.5x faster time-to-first-answer-token and a 45% increase in output speed compared to its predecessor Gemini 2.5 Flash, while cutting costs to just $0.25 per million input tokens and $1.50 per million output tokens — making it one of the most affordable capable AI models available for developers.
Built for Scale
Gemini 3.1 Flash-Lite is purpose-built for high-volume developer workloads where latency and cost efficiency are paramount. Google says the model can generate up to 363 tokens per second, placing it two to five times faster than many competing models at the same price tier. The model is designed to handle tasks including translation, content moderation, user interface generation, and data classification at scale — use cases where inference speed directly affects user experience.
Pricing Context
At $0.25 per million input tokens, Gemini 3.1 Flash-Lite is priced at roughly one-eighth the cost of Gemini Pro, opening up enterprise-grade AI capabilities to startups and developers who previously found large language model costs prohibitive. The output price of $1.50 per million tokens remains competitive with other budget-tier models from major providers.
Availability
The model is available in preview to developers via the Gemini API in Google AI Studio and to enterprise customers through Vertex AI. Google has stated that Gemini 3.1 Flash-Lite will be rolled out for broader general availability following the preview period, with additional language support and capability expansions expected.
The Race to the Bottom on AI Costs
The Gemini 3.1 Flash-Lite launch reflects the intensifying price competition among the major AI providers. As OpenAI, Anthropic, Google, and Meta compete aggressively for developer mindshare, the cost of accessing frontier AI capabilities has dropped dramatically over the past 18 months — a trend that is accelerating AI adoption across industries and geographies.
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